Resource release 
After 4 modes are executed sequentially, the Tensors \(w\) , \(x\)  and Node \(f_1\)  have no reference on them in Fig. REF . The Tensor \(y\)  may have a reference determind by derivative function of \(f_3\) .
It is known that PyTorch exploits the reference count and garbage collector mechanism of Python. PyTorch can make sure that all intermediate variables are released as soon as they become unneeded [1]}. When the Tensor \(w\) , \(x\)  and node \(f_1\)  are released, the STT and FTR referenced by Tensor \(w\) , \(x\)  are also released automatically and recursively.
